WO2019087250A1 - Système et procédé d'opération d'évitement de congestion - Google Patents

Système et procédé d'opération d'évitement de congestion Download PDF

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Publication number
WO2019087250A1
WO2019087250A1 PCT/JP2017/039128 JP2017039128W WO2019087250A1 WO 2019087250 A1 WO2019087250 A1 WO 2019087250A1 JP 2017039128 W JP2017039128 W JP 2017039128W WO 2019087250 A1 WO2019087250 A1 WO 2019087250A1
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Prior art keywords
congestion
elevator
floor
users
traffic
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PCT/JP2017/039128
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English (en)
Japanese (ja)
Inventor
貴大 羽鳥
孝道 星野
訓 鳥谷部
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株式会社日立製作所
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Priority to PCT/JP2017/039128 priority Critical patent/WO2019087250A1/fr
Priority to CN201780095708.1A priority patent/CN111201191B/zh
Priority to JP2019550003A priority patent/JP6960463B2/ja
Publication of WO2019087250A1 publication Critical patent/WO2019087250A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B1/00—Control systems of elevators in general
    • B66B1/02—Control systems without regulation, i.e. without retroactive action
    • B66B1/06—Control systems without regulation, i.e. without retroactive action electric
    • B66B1/14—Control systems without regulation, i.e. without retroactive action electric with devices, e.g. push-buttons, for indirect control of movements
    • B66B1/18—Control systems without regulation, i.e. without retroactive action electric with devices, e.g. push-buttons, for indirect control of movements with means for storing pulses controlling the movements of several cars or cages
    • B66B1/20—Control systems without regulation, i.e. without retroactive action electric with devices, e.g. push-buttons, for indirect control of movements with means for storing pulses controlling the movements of several cars or cages and for varying the manner of operation to suit particular traffic conditions, e.g. "one-way rush-hour traffic"
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B3/00—Applications of devices for indicating or signalling operating conditions of elevators

Definitions

  • the present invention relates to an elevator apparatus, and more particularly to a congestion avoiding operation system and method and method for appropriately performing a car allocation at crowded elevator landings and realizing a stay avoiding operation.
  • Patent Document 1 aims to obtain an elevator control device capable of allocating an appropriate number of cars to a crowded floor with respect to an elevator system having a plurality of elevators as one group.
  • Ground area camera 1B for detecting a crowded state in the car, camera 1A in the car, and a ground area area detecting means 3A for measuring the passenger area of the current elevator hall and the occupied area in the car based on the outputs of these cameras Detection means 3B, additional allocation determination means 3C for predicting future congestion levels of both the elevator hall and the car based on the output of the detection means and the past learning results, traffic information learning means 3G, and the prediction results
  • an operation control means 3E for allocating a plurality of cars to the landing.
  • Patent Document 2 aims to obtain a group management control device for elevators that performs appropriate service by allocating vehicles without restriction for division into service zones regardless of the presence or absence of a call. And a group management control apparatus for elevators that group-controls a plurality of elevators that drive back and forth between the two, and the traffic flow discrimination unit 1 that discriminates the traffic flow of the users of the elevators;
  • the vehicle comprises: a dispatch number control unit 2 that sets the number of elevators to be dispatched based on the determination result of the traffic flow; and a car dispatch unit 3 that dispatches the vehicles based on the number of dispatches set by the dispatch number control unit 2
  • the flow determining unit 1 obtains upper floor boarding load and lower floor boarding load based on floor data and boarding load data, and determines the traffic flow based on the upper floor boarding load and lower floor boarding load.
  • Crowded floor, up peak or down peak service, normal times, to detect the off-time, the dispatch unit count control section 2 sets the appropriate vehicle allocation number to
  • Patent Document 1 it is inadequate as a response to non-routine sudden events.
  • the past learning results in the method of Patent Document 1 do not include sudden events other than the routine, and prediction of the sudden events is impossible.
  • Patent Document 1 since the users gather at the landing and the call is generated and then the response is taken, there is a high possibility that congestion has occurred, and it is effective for the appropriate number of vehicles to be dispatched. , It is insufficient as a response to prevent congestion.
  • a congestion avoiding operation system in a facility provided with a plurality of elevator apparatuses which is a congestion detecting unit for detecting congestion in a hall of elevators in the facility, and a crowded floor detected as congestion
  • a congestion detecting unit for detecting congestion in a hall of elevators in the facility
  • a crowded floor detected as congestion
  • the number of users of the crowded floor is equal to or higher than an arbitrary threshold or a judgment unit which determines the degree of congestion on the crowded floor based on the number of elevator users on the crowded floor
  • a control unit for executing the traffic avoidance operation by the elevator device, and in the traffic avoidance operation, a plurality of elevator devices are sequentially allocated to the congested floor.
  • a method for avoiding traffic jams in a facility equipped with a plurality of elevator devices which requires crowded floors and the number of users as congestion at elevators in the facility, and the number of users above an arbitrary threshold value Determine whether there is a certain number of users and carry out congestion avoidance operation with multiple elevator devices if the number of users is more than an arbitrary threshold, and in congestion avoidance operation, allocate multiple elevator devices to a congested floor that is sequentially detected Traffic congestion avoidance driving method characterized by
  • FIG. 7 is a diagram showing an example of a storage format of past experience data learned by a learning unit 31.
  • FIG. 7 is a flow diagram specifically exemplifying processing content in the floor-specific floor-number estimation unit 32 of FIG.
  • FIG. 6 is a view showing an example of a boarding rate set by a boarding rate setting unit 40; The figure which shows the example of a flow which shows the processing content of the boarding number determination part 39 and the driving
  • FIG. 7 is a diagram showing a processing flow for realizing a retention avoiding operation in the retention avoiding operation command unit 41 of FIG. 1.
  • FIG. 1 shows a schematic configuration of a congestion avoiding operation system of an elevator apparatus according to the present invention.
  • FIG. 1 facilities and systems in a facility such as a building 1 and an external system 2 are described.
  • facilities and systems in facilities such as building 1 are elevator operation management system 3, landing elevator service request device 4 on each floor, surveillance camera 5 on each floor, building management system 6, etc.
  • Data communication is performed mutually via 8.
  • a plurality of elevator control systems 7a to 7n are installed and controlled by the elevator operation management system 3.
  • FIG. 1 illustrates a public organization management system as an example of the external system 2.
  • the elevator operation management system 3 and the elevator control systems 7a to 7n realize the congestion avoiding operation of the elevator apparatus, and this part is mainly responsible for the congestion avoiding operation system according to the present invention.
  • the elevator operation control system 3 obtains an output by obtaining many inputs and settings. Among the input and output, between elevator control systems 7a to 7n and elevator operation management system 3, elevator control systems 7a to 7n report operation state information S71 to elevator operation management system 3, and the elevator control system In each of 7a to 7n, each elevator is controlled by a control command signal S72 from the elevator operation management system 3. What is characteristic here is that the elevator operation control system 3 operates and manages all the units in the building 1, and the other matters are the same as the normal elevator control, so the explanation here is Omit
  • all units in the building 1 are operated and managed, but an operation management system may exist in any elevator group such as low, middle and high tiers.
  • the service request signal S4 from the landing elevator service request device 4 of each floor, the video signal S5 from the monitoring camera 5 of each floor, the building management information 6 from the building management system 6, and the public organization management system 2 Public institution management information S2 etc. are obtained.
  • the landing elevator service request device 4 indicates, for example, an up-and-down button provided on the landing for implementing a service request in the vertical direction. Or the destination floor registration apparatus etc. which input a destination floor from a platform are mentioned.
  • FIG. 2 is a diagram showing a landing environment example suitable for the present invention.
  • surveillance cameras 5 (5-1, 5-2, 5-3, 5-4) for monitoring and photographing the space including the elevator door, and the up and down buttons 4 as the hall elevator service request device 4 (4-1, 4-2, 4-3, 4-4) are installed.
  • lanterns 20 (20-1, 20-2, 20-3) indicating the current movement direction of the elevator car are disposed.
  • an in-car camera 21 and a load sensor 22 are provided in the elevator car 24.
  • the positioning of the service request signal S4 in the present invention is for confirming the upward and downward directions of the elevator, and the up-and-down button 4 is illustrated in FIG. May be a destination floor registration device or the like.
  • the positioning of the video signal S5 in the present invention is for measuring the number of users, and any means capable of directly or indirectly confirming the number of users can be substituted.
  • information on the number of users can also be obtained from the in-car camera 21 provided in the elevator car 24 and the load sensor 22 provided in the lower part of the elevator car 24.
  • the upward and downward directions of the elevator can be confirmed, and from the video signal S5, the number of users can be confirmed, and from the building management information S6, the conference in the facility
  • the action schedule such as an event can be confirmed, and the operation information (for example, train delay) of the public organization on the day can be grasped from the public organization management information S2.
  • the reception unit 36 in the elevator operation management system 3 of FIG. 1 obtains the service request signal S4, the video signal S5, the building management information S6, etc. via the communication means 8, and the operation state from the elevator control systems 7a to 7n. Information S71 is input.
  • An input signal from the receiving unit 36 is given to the hall number determination unit 39 and the learning unit 31 and used. First, processing contents on the learning unit 31 side will be described.
  • the service request signal S4, the video signal S5, the building management information S6 and the like obtained through the communication means 8 are recorded in the learning unit 31 and used.
  • the service request signal S4 and the video signal S5 are stored together with information on time when these signals are generated, and are used as past experience information.
  • the past scenes day of the week, seasons, etc.
  • the user's actions at certain times, and the modes are statistically grasped. For example, it is possible to grasp an overview of the movement status of a person at work, at lunch time, at night, and the like. Therefore, in a similar future scene, it can be estimated that the user exhibits the same behavior pattern as the past experience.
  • Patent Document 1 the information used for the “past learning result” is such information.
  • the service request signal S4 and the video signal S5. These pieces of information can be said to be information on the operation results of the plurality of elevator apparatuses, and are information obtained within the range controlled and managed by the elevator operation management system.
  • the building management information S6 from the building management system 6 and the public organization management information S2 are further used in order to judge and deal with congestion in a predictive manner.
  • the service request signal S4 and the video signal S5 are used as experience information in the past, whereas the building management information S6 from the building management system 6 is an action schedule for a meeting, event, etc. in a facility in the near future (The place, the attendee and the place where they are present) are the information registered in the building management system 6. According to this, for example, people from each floor at the meeting on the fifth floor from 3 o'clock today Is predictable.
  • Event information includes planned information (building management information S6) and unexpected information (public organization management information S2), both of which are provided from an external system other than the elevator operation management system.
  • the building management information S6 and the public organization management information S2 are obtained together with information on the occurrence time or the end time of these events.
  • the learning unit 31 learns the number of people who use the normal elevator on a daily basis.
  • macro number information can be output.
  • the learning unit 31 learns the boarding rate by floor.
  • the number of passengers in the elevator car is detected or calculated by the load in the elevator or the camera in the car. Furthermore, in order to detect the number of people at the landing, the number of people at the landing is directly detected using a landing camera, a distance sensor, and the like. Alternatively, it may be a method of recognizing that there is a person at the landing when the landing button is pressed, from the button registration status of the landing.
  • the number of people in the landing In response to the landing button registration from each floor, when arrival and opening the door, it is determined whether the number of people in the landing will be exhausted or not. Record your boarding rate. Specifically, when there are 10 people on the 5th floor and 10 passengers in the car, when the car arrives on the 5th floor and there are 2 people in the platform, the number of people in the car is It will be 18 people. When the number of seats is 24 people, the boarding rate in the car will be 75%. Alternatively, instead of the number of people, the occupancy rate of the car user at that time or the vacancy rate in the car may be detected, and the occupancy rate or the vacancy rate may be recorded.
  • the recorded number of passengers, occupancy rate, and vacancy rate are taken as the ride rate, and these are learned daily by floor.
  • the boarding rate by floor is obtained by obtaining the utilization rate of each floor, and may be obtained by weighting by the number of users of each floor. Furthermore, the boarding rate by floor should be grasped separately for going up and down. For example, in the case of a building on the eighth floor, it is preferable to obtain the boarding rate in the upward direction and the boarding rate in the downward direction as the boarding rate on the fifth floor.
  • the administrator of the elevator operation management system sets the boarding rate using the boarding rate setting unit 40 with reference to the past boarding rate results accumulated in the learning unit 31 and the like.
  • the boarding rate to be set defines the degree of congestion at which the user decides to wait for the next vehicle allocation. For example, even if it is a 24-seater car, it is a limit boarding rate at which a person waiting for the next allocation appears when 18 people are on board. Even if the attendance rate is high, even if the occupancy rate is high, the occupancy rate may be low at the normal time, so the occupancy rate at the limit should be set according to the floor, the up and down, the hour, and so on.
  • FIG. 7 is an example of the boarding rate set by the boarding rate setting unit 40, in which the boarding rates by floor and by floor are set in a certain time zone. For example, a user using the 8th floor chooses to wait for the next car if it is 40% or more in the upward direction, and if it is 50% or more in the downward direction It is meant to choose to wait for the next car.
  • the information on the boarding rate is used in the scene of determining the number of vehicles to be described later.
  • the past experience data learned by the learning unit 31 is, for example, organized and stored as shown in FIG. FIG. 3 exemplifies, for example, a storage format of the past record number of passengers, and for each date and time in the past, stores the number of passengers on each floor and the information of the boarding rates by floor and by going up and down. There is.
  • the storage format of the past actual number of people is also created in the same format.
  • the above-mentioned storage format may include information grasped and stored for each day, for example, every 10 minutes, and stored for a long time in the past.
  • the past experience data may include event information such as a meeting or various events as incidental information.
  • the past experience data learned by the learning unit 31 is used as a past experience in the prediction process in the following process.
  • the floor-level estimated-number-of-persons prediction unit 32 predicts, for example, the movement of people today according to the floor level from the past experience, the meeting schedule on the day, and the like.
  • FIG. 4a shows an example of the predicted number of passengers table TB1 predicted by the floor-based number of people predicting unit 32
  • FIG. 4b shows an example of the predicted number of people coming out table TB2 predicted by the floor-based number of people predicting unit 32.
  • the predicted number of people table TB1 and the predicted number of people table TB2 are time data D1 and D6, floor data D2 and D7, predicted number data D3 and D8, actual number data D4 and D9, predicted accuracy data D5 and D10, from the upper row. It is comprised by the boarding rate D11 and D12.
  • the floor-specific people number prediction unit 32 forms the data from the top to the third row of these tables using the past experience data in FIG. 3 and the like.
  • the number of people on each floor is 20 and 9 respectively at 8 o'clock (which will be described later, for example, 10 minutes from 8 o'clock).
  • 7, 14, 13, 7, 8 and 5 people are predicted to be.
  • the number of people getting off each floor is 20, It shows that it was predicted to be 5, 9, 15, 11, 15, 18, 11.
  • the method of creating the predicted number of passengers table TB1 and the predicted number of people table TB2 as described above, it can be created in consideration of past experiences and today's schedule, and further in consideration of today's train delay and the like. It can be determined by correction.
  • FIG. 5 is a flow diagram specifically exemplifying the processing content in the floor-based number-of-peoples prediction unit 32 of FIG. 1.
  • the processing in the learning unit 31 the time-series number of users measured daily is grasped together with the information of the boarding rate for each floor and in the up and down directions, and the past experience data of FIG. It shall be done. That is, it is assumed that past experience data corresponding to the actual number of people data D4 and D9 are secured and stored in time series and for equivalent days for the predicted number of people table TB1 and the predicted number of people table TB2. In addition, it is assumed that the past days are stored including information on events and meetings held on that day.
  • start of the process of FIG. 5 may be performed at an appropriate timing, for example, if provided as information for one day on the previous day, the process will be processed at an appropriate time on the previous day. Alternatively, if it is provided by an external request, it may be started when there is a request. In addition, if a new state change occurs, it should be reviewed each time even on the day.
  • processing step S100 of the floor-specific people estimation unit 32 past experience data and the like are fetched. These include actual number of people data D4, D9, time data D1, D6, boarding rate, building management information S6 and the like in the past.
  • processing step S101 setting information such as time width and designated time is fetched.
  • the output date (for example, tomorrow) is determined. It is determined whether the output date is a weekday, a holiday, or a pause, etc., and only the conditions of the corresponding condition are extracted from the past experience data of FIG.
  • processing step S103 for example, if the output date is a weekday, only past experience data of a weekday is extracted, and if the output date is a holiday, only past experience data of a holiday is extracted. If seasonal and day-to-day variations appear prominently for the user, these points should be taken into consideration.
  • the usage average by time is obtained for the extracted time-series usage records for a plurality of days, and the predicted number of passengers data table TB1 and predicted number of people data D3 and D8 of the predicted number of people table TB2 are obtained.
  • the said process is performed about the number of users for every floor, floor data D2 and D7 are also obtained collectively.
  • processing step S105 the presence or absence of the building management information S6 is confirmed.
  • the movement of the user according to the scale of the holding in processing step S106.
  • the predicted number of passengers data table TB1 and predicted number of people data table D2 of the forecasted number of people table TB2 obtained in the processing step S104 are corrected by reflecting the method of use.
  • the predicted number of people on the table TB1 It is preferable to correct the forecasted number of persons data D3 and D8 of the table TB2.
  • processing step S107 the presence or absence of public organization management information S2 is confirmed.
  • processing step S108 is performed. According to the degree of the delay, reflecting the movement of the user and the way of using the elevator, the predicted number of people table TB1 and the predicted number of people data table D3 and D8 of the predicted number of people table TB2 obtained in the processing steps S104 and S106. Fix it.
  • the processing of the processing steps S107 and S108 is executed by the external information acquired on the day.
  • the past performance is corrected based on the action schedule and the information of the public organization, and the predicted number of people data D3 and D8 of the predicted number of people table TB1 and the predicted number of people table TB2 are obtained.
  • the data of the boarding rate set by the boarding rate setting unit 40 corresponds to the predicted number of people table TB1 and the predicted number of people table TB2
  • the boarding rates D11 and D12 are reflected in the column.
  • the floor-specific people number prediction unit 32 further has an accuracy verification function, and based on the actual experience of predicting the lower three-level information to the upper three-level data created by the floor-specific people number prediction unit 32, Add data.
  • 6a shows an example of a predicted number of passengers table TB1 including actual data added by accuracy verification
  • FIG. 6b shows an example of a predicted number of people table TB2 including actual data added by accuracy verification.
  • the number of droppings of each floor is , 20, 5, 9, 15, 11, 15, 18 and 11, respectively, but actually they are 17, 13, 15, 12, 12, 17, 19 and 10, and their respective accuracy Of 89, 69, 70, 74, 93, 50, 80, 56%.
  • the addition of the data D4 and D9 in the tables of FIGS. 6a and 6b means that the learning unit 31 additionally writes the data as new past experience data.
  • the number-of-persons judgment unit 39 predicts congestion predicted by the number of people predicted by the number-of-persons prediction unit 32, or the number of people at the current point detected by the hall camera within the operation management system. Recognize.
  • the driving switching determination unit 37 selects the driving method according to the number of people in the hall obtained from the landing number of people determining unit 39, activates either the return driving instruction unit 42 or the staying avoidance driving instruction unit 41, and issues a return driving instruction.
  • the advance dispatching unit 38 issues a dispatching instruction in accordance with a command signal given by the unit 42 or the stay avoiding operation commanding unit 41.
  • FIG. 8, FIG. 9, and FIG. 10 show an example of the flow showing the processing contents of the number of passengers determination unit 39 and the operation switching determination unit 37. Since these only differ in the determination of the portion of the processing step S201, FIG. 8 will be mainly described, and FIGS. 9 and 10 will be described only the differences.
  • the start of the process of FIG. 8 may be performed at an appropriate timing, but may be started in advance in a scene where congestion predicted by the floor-by-floor number prediction unit 32 is expected. For example, in addition to daily routine events such as morning and evening work and lunch, it is preferable to start and start processing immediately before the expected congestion time based on the start and end of a meeting or event, etc. and train delays.
  • the learning unit 31 For the daily routine events described above, by learning the building-specific routine for each building daily by the learning unit 31, it is possible to grasp rough traffic flow using the elevator.
  • the start and end of a meeting, an event, etc. are input to the elevator side by detection or setting from an external system other than learning of the elevator, and the following flow is activated based on the input information.
  • processing step S200 it is determined whether a person is newly detected at the landing. This determines the number of people detected by the prediction from the learning unit described above or the input information from the external system. If it is not detected, the elevator will operate as it is.
  • processing step S201 it is determined which of return operation and retention avoidance operation should be performed depending on the number of people. Specifically, in FIG. 8, it is determined whether or not the detected number of people can be dispatched at one time.
  • a number is the total number of the elevators in each hall, and it is known with the number of capacity.
  • the number of people is set according to time, by floor, and by getting on and off as shown in FIG. .
  • the reason for taking the passenger ratio into account for the number of occupants is based on the user's psychology, as there is a tendency not to board in the car crowded state to a certain extent (waiting for the next) as the user's psychology. As a more practical operation, a large number of cars will be allocated.
  • the maximum number of persons that can be allocated at one time is theoretically 24 * 3 and can be carried by 72 people.
  • the determination as to whether or not the number of people that can be allocated at one time here is to determine whether the number of persons that can be allocated at one time calculated above just exceeds 72. If it exceeds 73 people, it will be determined that dispatch is not possible at one time.
  • a scene where every 24 people can be packed is unrealistic, and the maximum number of people who can actually get different differs depending on the user's psychology depending on buildings, time zones, and floors. Therefore, the learned boarding rate is used to evaluate the possible number of boarders that can be closer to reality.
  • the above-described method makes it possible to distribute at one time, but the number of users is 70 when the boarding rate on this floor is 70% from the past learning results. Assuming that the case is, it is assumed to be divided into 16 people, 16 people, 16 people, 16 people and 6 people, and it can not be distributed at one time, but is predicted to be divided into 5 times.
  • the pre-dispatching operation is performed in the processing step S203.
  • the retention avoidance operation is performed in processing step S102.
  • the maximum number of passengers (24 * 0.7 * 3) is 51 when the capacity is 24 people, the boarding ratio of this floor is 70%, and the number is three.
  • the threshold is 51, which is defined as the maximum passenger (24 * 0.7 * 3), and the threshold is any one or more of the number of people in elevator specification, the loading capacity, and the boarding rate in the elevator car It is good to adopt including.
  • the pre-allocation operation is executed in processing step S202.
  • processing step S201 of FIG. 8 comparison is made based on the actual number of detected people, but in processing step S201A of FIG. 9, the number of people predicted to occur within one cycle of the elevator is used as a reference.
  • the predicted number of users is referred to because the number of people is obtained separately by time, by floor, and by getting in and out of the floor by the floor number estimation unit 32, as shown in FIGS. 4a and 4b.
  • the number of users is not limited to the number of persons based on past experience data, but is also considered to be the number of persons transiently increasing due to an event or the like in the near future based on public organization management information S2 and building management information S6.
  • FIGS. 12 and 13 time is taken on the horizontal axis.
  • An area indicated by a symbol A represents a waiting state on the congested floor.
  • An area indicated by symbol B indicates, for example, the height direction positions of three elevator cars.
  • Region C represents the initial state of congestion on the congested floor.
  • one elevator car is first allocated at time t0, and the first one gets off the crowded floor at time tn1 upon boarding here, and thereafter two units
  • the third and third units are sequentially dispatched at fixed time intervals, and are operated to leave the crowded floor at times tn2 and tn3, respectively. After that, the first one is allocated to the congested floor again and the congestion is eliminated by the second round at time t2.
  • the congestion avoidance operation is performed by the plurality of elevator apparatuses when the threshold is equal to or more than the threshold, and the plurality of elevator apparatuses are sequentially allocated to the congestion floor in the congestion avoidance operation. It is a thing.
  • FIG. 11 is a diagram showing a processing flow for realizing the retention avoiding operation (processing steps S202 in FIG. 8, FIG. 9, and FIG. 10) in the retention avoiding operation command unit 41 in FIG.
  • the flow of FIG. 11 is started when congestion can not be eliminated by a plurality of vehicles being dispatched at one time, and in the first processing step S300, the number of services participating in the retention avoiding operation is determined.
  • the number of services may not be all but multiple. For example, when there are elevators that can not be serviced due to maintenance or failure, it is possible to make a more realistic evaluation by removing them from the control target.
  • the target floor which should eliminate congestion is set.
  • the target floor is the floor whose congestion has been newly detected in S200.
  • the average interval time limit RTT is determined using equation (1).
  • RTT (((S / f) * V) + (f * Tdoor * ⁇ )) / r (1)
  • S is the predicted maximum travel distance
  • F is the predicted stop floor
  • V is the speed
  • T door is the door opening time
  • ⁇ is the on-site adjusting door opening time
  • r is the number of operating units.
  • This method is generally used for traffic calculation formulas used for elevator installation plans. However, the method is not limited to this, and another method may be used to obtain the average interval time of elevators. For example, a method may be employed in which the operation status of the elevator is learned and the operation interval is recorded for each floor.
  • processing step S303 the advancer is set to a unit whose arrival is earlier than the target floor. However, new allocation to other floors is excluded, in order to give priority to service relaxation to the target floor.
  • processing step S304 the dispatching device is instructed to dispatch to the target floor, and in processing step S305, the next aircraft is set to the second arriving arrival earlier than the target floor, and in processing step S306, the average interval timed timer is started. .
  • processing step S307 the expiration of the average interval timed timer is confirmed, and in the case of expiration, the next car is set as the first aircraft in processing step S309.
  • the processing returns to processing step S304, and the processing up to processing step S306 is repeatedly executed.
  • the next car is made to stand by at the doorway ⁇ 2 of the target floor in processing step S308.
  • new allocations are excluded.
  • the elevator cars can be arranged on the congested floor sequentially at fixed time intervals as shown in FIG.
  • the return driving in the return driving command unit 42 in FIG. 1 is obtained by executing the advance allocation driving in the processing step S203 in FIGS. 8, 9 and 10.
  • the normal operation which operates in response to a call from each floor is left, for example, operated according to a specific instruction from security, and after the end, the normal operation is resumed.
  • the return operation (pre-dispatching operation) is performed when the number of users on the congested floor is equal to or less than a threshold.
  • Elevator operation management system 4 Station elevator service request device on each floor 5: Surveillance camera on each floor 6: Building management system 7a ⁇ 7n elevator control system, 8: communication means, 31: learning unit, 32: number of people predicting unit by floor, 36: receiving unit, 37: operation switching judging unit, 38: advance allocation instruction unit, 39: number of people in hall Judgment part, 41: Staying avoidance operation command part, 42: Return operation command part, S2: Public organization management information, S4: Service request signal, S5: Video signal, S6: Building management information, S72: Control command signal

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  • Automation & Control Theory (AREA)
  • Elevator Control (AREA)
  • Indicating And Signalling Devices For Elevators (AREA)

Abstract

Le but de la présente invention est de fournir un système et un procédé d'opération d'évitement de congestion pour un dispositif d'ascenseur, le système et le procédé réalisant une opération d'évitement de stagnation avec laquelle il est possible de réduire le stress des utilisateurs provoqué par des temps d'attente longs. L'invention concerne un système d'opération d'évitement de congestion dans une installation équipée d'une pluralité de dispositifs d'ascenseur, le système d'opération d'évitement de congestion étant caractérisé en ce qu'il comprend: une unité de détection d'encombrement qui détecte un encombrement sur une plate-forme d'un ascenseur à l'intérieur de l'installation; une unité de détermination qui détermine, sur la base d'un étage encombré où un encombrement a été détecté et du nombre d'utilisateurs de l'ascenseur sur l'étage encombré, un degré d'encombrement sur l'étage encombré provoqué par le nombre d'utilisateurs sur l'étage encombré atteignant ou dépassant une valeur seuil discrétionnaire; et une unité de commande qui exécute une opération d'évitement de congestion à l'aide de la pluralité de dispositifs d'ascenseur lorsque la valeur seuil est atteinte ou dépassée; la pluralité de dispositifs d'ascenseur étant expédiés en séquence vers l'étage encombré dans l'opération d'évitement de congestion.
PCT/JP2017/039128 2017-10-30 2017-10-30 Système et procédé d'opération d'évitement de congestion WO2019087250A1 (fr)

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PCT/JP2017/039128 WO2019087250A1 (fr) 2017-10-30 2017-10-30 Système et procédé d'opération d'évitement de congestion
CN201780095708.1A CN111201191B (zh) 2017-10-30 2017-10-30 拥堵避免运转系统和方法
JP2019550003A JP6960463B2 (ja) 2017-10-30 2017-10-30 渋滞回避運転システム及び方法

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JP2020193104A (ja) * 2019-05-30 2020-12-03 株式会社日立製作所 かご内状態検出システム、エレベーター及びかご内状態検出方法
WO2022097188A1 (fr) * 2020-11-04 2022-05-12 株式会社日立製作所 Ascenseur et procédé de commande d'ascenseur
JP2022094479A (ja) * 2020-12-15 2022-06-27 東芝エレベータ株式会社 群管理制御装置および群管理制御方法

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JP2020193104A (ja) * 2019-05-30 2020-12-03 株式会社日立製作所 かご内状態検出システム、エレベーター及びかご内状態検出方法
JP7083786B2 (ja) 2019-05-30 2022-06-13 株式会社日立製作所 かご内状態検出システム、エレベーター及びかご内状態検出方法
WO2022097188A1 (fr) * 2020-11-04 2022-05-12 株式会社日立製作所 Ascenseur et procédé de commande d'ascenseur
JPWO2022097188A1 (fr) * 2020-11-04 2022-05-12
JP7561206B2 (ja) 2020-11-04 2024-10-03 株式会社日立製作所 エレベーターおよびエレベーターの制御方法
JP2022094479A (ja) * 2020-12-15 2022-06-27 東芝エレベータ株式会社 群管理制御装置および群管理制御方法
JP7159271B2 (ja) 2020-12-15 2022-10-24 東芝エレベータ株式会社 群管理制御装置および群管理制御方法

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